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This study identifies six dynamic capabilities (DCs), which enable corporates' strategic change toward resilience in today's increasingly volatile, uncertain, complex, and ambiguous (VUCA) business environment. In this context, pertinent research has proven DCs' conduciveness for corporates to enhance their levels of resilience. Yet, there remain dispersed definitions of such DCs across research fields and a comprehensive synthesis has been missing. The present study addresses this gap through a systematic literature review of 71 articles published in peer-reviewed journals. It synthesizes six fundamental DCs and their underlying microfoundations fostering resilience, which are mediated by the corporates' idiosyncratic social capital. Our findings thus contribute to the extant literature by providing a synthesis of relevant DCs into an integrated theoretical framework, answering multiple calls in previous research for a better understanding of the corporate resilience-building process. By doing so, this study paves the way for future research to investigate the effects of DCs on the sustained competitive advantage of corporates in VUCA environments.
This research explores the characteristics of green influencer messages on follower engagement by examining the interplay between message framing (gain vs. loss), construal level (high vs. low), and post timing (weekdays vs. weekends). Green influencers (also: greenfluencers or sustainable influencers) are considered a key agent for a change to more sustainable consumption. A pilot field study of 1000 green influencers, however, indicates that the current communication practices of green influencers (which strongly focus on gain frames, low construal, and posts during the week) are not ideal for maximizing engagement and sustainable behavioral intentions. Two experiments replicate this finding and establish the process through which green influencer posts affect engagement: gain frames increase fluency, which increases engagement; low construal levels decrease psychological distance, which increases engagement. Timing moderates these processes in that weekend posts increase the engagement with gain frames and week posts increase the engagement with low-construal frames. These findings highlight that there is no silver bullet in green influencer messages, but that green influencers need to adapt the framing and construal of their messages to the posts' timing to increase their contribution to more sustainable lifestyles and the greater good.
In today's data-driven era, ubiquitous concern about environmental issues pushes more startups to engage in business model innovation that promotes environmentally friendly technologies. The goal of these startups is to create technology-based products and services that enhance environmental sustainability. In this context, artificial intelligence promises to be a key instrument to create, capture, and deliver value. However, the existing literature lacks a deep understanding of how startups using AI innovate their business models to achieve a positive environmental impact. Therefore, this paper investigates how green technology startups utilize AI from a business model innovation perspective for environmental sustainability. We conduct a qualitative, exploratory multiple-case study using the Eisenhardt methodology, based on interview data analyzed using qualitative content analysis. We derive five predominant manifestations for AI-driven business model innovation and identify archetypical connections between business model dimensions. Further, we establish three overarching archetypical associations among the cases. In doing so, we contribute to theory and practice by providing a deeper account of how green technology startups attempt to maximize their positive environmental impact through AI. The results of this study also highlight how business model innovation driven by AI can support society in securing a more environmentally sustainable future.
Purpose
When CEOs are publicly weighing in on sociopolitical debates, this is known as CEO activism. The steadily growing number of such statements made in recent years has been subject to a flourishing academic debate. This field offers first profound findings from observational studies. However, the discussion of CEO activism lacks a thorough theoretical grounding, such as a shared concept accounting for the heterogeneity of sociopolitical incidents. Thus, the aim of this paper is to provide an archetypal framework for CEO activism.
Design/methodology/approach
The authors used a multiple case study approach on 145 activism cases stated by CEOs and found seven distinct statement archetypes.
Findings
The study identifies four main structural design elements accounting for the heterogeneity of activism, i.e. the addressed meta-category of the statement, the targeted outcome, the used tonality and the orientation of the CEOs’ positions. Further, the authors found seven distinguishable archetypes of CEO activism statements: “Climate Alerts”, “Economy Visions”, “Political Comments”, “Self-reflections and Social Concerns”, “Tech Designs”, “Unclouded Evaluations” and “Descriptive Explanations”.
Research limitations/implications
This typology classifies the heterogeneity of CEO activism. It will enable the analysis of interrelationships, mechanisms and motivations on a differentiated level and raise the comprehensibility of research-results.
Practical implications
The framework supports executives in understanding the heterogeneity of CEO activism and to analyse personality-fits.
Originality/value
To the authors’ knowledge, this marks the first conceptualisation of activism developed cross-thematically. The work supports further theory-building on CEO activism.
The new normal
(2024)
The recent surge in artificial intelligence (AI) adoption by small and medium-sized enterprises (SMEs) has garnered significant research attention. However, the existing literature reveals a fragmented landscape that hinders our understanding and application of insights about AI use in SMEs. We address this through a systematic literature review, wherein we analyze 102 peer-reviewed articles on AI adoption in SMEs and categorize states and trends into eight clusters—(1) compatibility, (2) AI readiness, (3) knowledge, (4) resources, (5) culture, (6) competition, (7) regulation, and (8) ecosystem—according to the technology–organization–environment model. Our research reveals valuable insights but also identifies significant gaps in existing literature, notably the oversight of trends identification as a pivotal driver and the neglect of legal requirements. Our study clarifies the AI implementation within SMEs, offering a holistic and theoretically grounded perspective to empower researchers and practitioners to facilitate more effective AI adoption and application within the SME sector.
Translating AI ethics principles into practice to support robotic process automation implementation
(2024)
When organizations leverage artificial intelligence (AI) to automate processes previously performed by people, it frequently causes uncertainty and fear among those affected. An often suggested way for organizations to navigate such challenges is to seek guidance from AI ethics principles. Leaders, however, find it difficult to make practical use of these abstract, high-level principles. Based on a case study of the large-scale implementation of robotic process automation at an energy service provider in Germany, we provide recommendations for translating AI ethics principles into practice.
Recent years have seen a surge in research on artificial intelligence (AI)-driven business model innovation (BMI), reflecting its profound impact across industries. However, the field’s current state remains fragmented due to varied conceptual lenses and units of analysis. Existing literature predominantly emphasizes the technological aspects of AI implementation in business models (BMs), treating BMI as a byproduct. Additionally, there is a lack of coherent understanding regarding the scope of BMI propelled by AI. To address these gaps, our study systematically reviews 180 articles, offering two key contributions: (1) a structured analysis of evolving research dimensions in AI-driven BMI, differentiating between static and dynamic views of BMI, and (2) a framework presenting distinct research perspectives on AI-driven BMI, each addressing specific managerial focuses. This synthesis facilitates a comprehensive understanding of the field, enabling the identification of research gaps and proposing future avenues for advancing knowledge on the management of AI-driven BMI.
Climate-related issues have become increasingly relevant, as reflected in current political and academic discourse. This development is also reflected in investors' capital allocation decisions and their demand for climate-related information. Considering the recommendations of the Task Force on Climate-related Financial Disclosures (TCFD), we first investigate the climate-related disclosure quality of listed German firms. We use self-constructed scoring models based on the TCFD recommendations to measure disclosure quality. Second, we use regression analysis to investigate whether corporate governance can explain climate-related disclosure quality. The results indicate that disclosure quality is heavily dispersed across firms, with risk disclosure being better than disclosure of opportunities. Corporate governance factors exert distinct but mostly weak influence on climate-related disclosure quality and that institutional ownership promotes climate-related disclosure quality. We show several implications for research and practice and highlight the relevance for firms to implement a comprehensive approach to communicating climate-related issues.
A gamification approach for enhancing older adults' technology adoption and knowledge transfer
(2024)
Technology is assumed to be important for enhancing older adults' life quality and for ameliorating age-related problems, but older adults nevertheless typically exhibit lower technology adoption rates than young people. Gamification has the potential to address this problem by motivating older adults, but its value for the elderly has thus far been undermined through gamification design biases favoring young people. This study addressed this problem by developing a purpose-built gamified learning system, based on a popular mobile payment platform, to test the potential of employing a gamification-and-learning approach to the design of gamification systems for enhancing knowledge transfer and technology adoption by older adults. The research employed structural equation modeling, incorporating user knowledge and gamification-related constructs, drawing upon the established Technology Acceptance Model. Data were collected from older adults in Hong Kong with an appropriate demographic and market profile, following a one-group pretest–posttest research design. The results revealed notable gamification-induced improvements in the knowledge and technology adoption intentions of older adults, and significant positive relationships between gamification effectiveness and technology adoption constructs. The research demonstrates the significant positive effects which gamification may have on the acceptance and usage of technology by older adults and evokes policy implications for the silver-hair market.
Purpose
In public management research, the focus in the public value debate has been on public administration organizations’ broader societal outcomes. Public value describes how public administrations form a vital part of the social context in which people develop and grow. However, there has not yet been an analysis of how public administration contributes to happiness in society.
Design/methodology/approach
In this study, we empirically analyze the relationship between people’s happiness and the public value of public administration. Our approach is based on a unique Swiss survey dataset comprising 870 individuals.
Findings
We find a positive relationship between public administration’s public value and happiness. We also find preliminary evidence with a moderation analysis that the relationship between a value-creating public administration sector and self-reported happiness is stronger for public administration employees.
Research limitations/implications
While correlation studies cannot claim causal explanations and common method bias may additionally limit any research in social science, we took a number of measures to mitigate related problem. We tested our model in two samples and took both several procedural techniques and a survey design minimizing common method bias.
Practical implications
The paper discusses implications for public sector performance measurement for public management and practitioners.
Social implications
This study calls for a more positive view on the multiple functions public administration performs for society. After an era of critical voices, our study helps reclaim public administration as a positive force for society at large in times of grand challenges, such as climate crisis, demographics and digitization.
Originality/value
This study has highlighted the importance between public administration’s public value and happiness in Swiss public service organizations. The study also showed that an employment in the public administration contributes to the happiness of individuals and beyond to society.